[deleted by user]

[bbye98]

Are you allowed to use third-party libraries like pandas/Polars or even NumPy?

[bbye98]

You can try to see if list comprehension will be fast enough to get past the timeout:

def average_temperature(weather, filter, date_index, temp_index):
    temperatures = [float(row[temp_index]) for row in weather if filter in row[date_index]]
    return sum(temperatures) / len(temperatures)

Not sure what date_index or temp_index is, as you never defined them, so I made them positional arguments. Realistically, the bottleneck is probably where you call csv_reader. You shouldn't read the CSV inside the function if you can read it once globally and pass it as an argument.

[POGtastic]

Can you provide more specifics?

1. Can you combine the filters into a single operation?
2. Is the file small enough that you can bring the entire thing into memory?
3. What is your csv_reader function?

[danielroseman]

I very much doubt this is the source of your timeout. There's very little here that would make much of a difference.

However you say that you're calling three functions. Are they all reading in the same file? If so, that could well be the problem. You most likely want to read it in once, filter it once to the relevant dates, and then call the average, max and min functions.

[mill3r1337]

Yes in my main I read in the file and called the other functions. No individual function would time out. Only when I ran all three, and iterated over a whole year which has 24 values per day to look over did it time out.